Automated system and method for clarity measurements and clarity grading

ABSTRACT

A computer-based system and method for taking clarity measurements of a gem, and a computer-readable medium having computer-executable instructions, are provided and include receiving a pixilated image of a gem and identifying pixels representing an inclusion. The method and medium further include determining characteristics of the inclusion as a function of the pixels representing the inclusion, and providing a clarity grade based upon the determined characteristics. Also provided is a method for mapping a gem, and a computer-readable medium having computer-executable instructions, which include receiving a pixilated image of a gem having facet edges, and identifying pixels representing the facet edges. The method and medium further include generating a diagram of the gem, such that the diagram is a function of the pixels representing the facet edges, and superimposing the diagram onto the pixilated image.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S. Pat.Application No. 17/103,737 filed on Nov. 24, 2020, which is acontinuation of and claims priority to U.S. Pat. Application No.16/351,406 filed on Mar. 12, 2019 (now U.S. Pat. No. 10,891,724), whichitself is a continuation of and claims priority to U.S. Pat. ApplicationNo. 15/918,932 filed on Mar. 12, 2018 (now U.S. Pat. No. 10,275,870),which itself is a continuation of U.S. Pat. Application No. 12/287,186filed on Oct. 7, 2008 (now U.S. Pat. No. 9,953,406), all of which arehereby incorporated by reference in their entireties.

TECHNICAL FIELD

The present invention is directed generally towards analyzing a gem, andmore specifically towards utilizing a pixilated image to map a gem andto determine various inclusion characteristics associated with the gemand towards determining a clarity grade from the determined inclusioncharacteristics.

BACKGROUND OF THE TECHNOLOGY

Today, vision analysis has a growing impact on production, productioncontrol, and quality control issues within many industries. The Diamondand Gem industry is no exception, and has adopted digital imaging andvision analysis technology to improve the efficiency of manufacturingprocesses and improve quality controlling stations. Examples are thehigh tech computer measuring devices that have taken over the proportionmeasuring from classic instruments, such as the Gemological Institute ofAmerica Proportionscope. Powerful computers and high resolution digitalimages are now available and have triggered the development of morehighly sophisticated vision analysis tools and advanced vision analysissoftware programs.

The theoretical and practical knowledge in the vision industry is vast,but applying these optical tools and vision analysis knowledge todiamond clarity grading is rather new. There are many considerations incapturing a suitable clarity image, such as lighting and the cost ofhardware. Some of these considerations even involve compromises with howelse the image can be used. A detailed image of only the grade settinginclusion may be useful for grading clarity, but capturing the wholediamond allows for a broader range of applications, such as placing amore attractive image on a report or capturing symmetry faults.Capturing the whole image is also critical for determining the relativesize of the inclusion.

In view of the rapidly growing technological landscape of visionanalysis and digital imaging acquisition, developing support tools forclarity grading via vision analysis could be particularly helpful. Suchtools, may for example, help to better understand the visual claritygrading decision processes, and also help provide consistency in theseprocesses by providing these tools to grader trainees uniformly. Othermethodologies such as x-ray scanning or infrared imaging are inherentlylimited since they cannot duplicate what a diamond grader sees in thelaboratory, whereas vision analysis can replace the human eye with acamera, and a computer application can simulate the decision makingprocesses. The alternative methodologies also are often too costly toconsider. Accordingly, there is currently a need for a method and systemfor analyzing a gem via vision analysis software in support of claritygrading activities.

SUMMARY OF THE INVENTION

This invention addresses the aforementioned problems by providing animproved method and system for analyzing a gem.

In an embodiment of the invention, a method is provided for takingclarity measurements of a gem. The method includes receiving a pixilatedimage of a gem, designating a region of interest in the pixilated imageof the gem which includes an inclusion, analyzing the designated regionof interest for pixels that correspond to the inclusion, and determiningcharacteristics of the inclusion as a function of the pixels thatcorrespond to the inclusion.

In a further embodiment of the invention, the analyzing step includesevaluating the designated region of interest using a plurality of visionanalysis scripts, wherein each of the plurality of vision analysisscripts include different combinations of pixel analysis algorithms. Thedifferent combinations of pixel analysis algorithms in each of theplurality of vision analysis scripts are preferably capable of detectingdifferent types and patterns of inclusions.

In an embodiment of the invention, a method is provided for takingclarity measurements of a gem which includes receiving a pixilated imageof a gem, designating a region of interest in the pixilated image of thegem which includes an inclusion, analyzing the designated region ofinterest for pixels that correspond to the inclusion, and determiningcharacteristics of the inclusion as a function of the pixels thatcorrespond to the inclusion, wherein a precision measurement value of adimension of the gem is received, a dimension in pixels of the gem isextracted from the pixilated image of the gem, and an image calibrationvalue is generated based upon the precision measurement value and thedimension in pixels. A relative size for the inclusion can be determinedas a function of a quantity of pixels representing the inclusion, aquantity of pixels representing the gem, and the image calibrationvalue.

In connection with the embodiments of the present invention,determination of inclusion characteristics may include correlating aplurality of inclusion location identifier regions to areas of thepixilated image of the gem, and identifying an inclusion position forthe inclusion as a function of the correlated plurality of inclusionlocation identifier regions.

In connection with the embodiments of the present invention,determination of inclusion characteristics may include quantifying abrightness of the pixels corresponding to the inclusion, quantifying abrightness of pixels in a designated area adjacent the pixelscorresponding to the inclusion, and determining a relief characteristicfor the inclusion as a function of the brightness of the pixelscorresponding to the inclusion and of the pixels in the designated area.

A still further embodiment of the present invention further includesgenerating a clarity grade from the determined characteristics of theinclusion.

Still another embodiment of the present invention further includesconstructing a gem structure diagram for the gem from the pixilatedimage of the gem, and combining the gem structure diagram and thepixilated image of the gem, wherein inclusion characteristics of thedetermining characteristics operation are determined using informationfrom the combined gem structure diagram and pixilated image of the gem.

In another embodiment of the invention, a computer-readable medium isprovided having computer-executable instructions thereon for renderingdigital content on a device. Included are computer-executableinstructions for receiving a pixilated image of a gem;computer-executable instructions for identifying pixels representing aninclusion within a designated region of interest that includes theinclusion, and computer-executable instructions for determiningcharacteristics of the inclusion as a function of the pixelsrepresenting the inclusion.

In a further embodiment of the invention, a method for mapping a gem isprovided. Within such embodiment, the method includes the steps ofreceiving a pixilated image of a gem having facet edges, and identifyingpixels representing the facet edges. The method also includes the stepsof generating a diagram of the gem, such that the diagram is a functionof the pixels representing the facet edges, and superimposing thediagram onto the pixilated image. Yet another embodiment of theinvention comprises computer-readable media having computer-executableinstructions thereon to perform gem mapping operations includingreceiving a pixilated image of a gem having facet edges, identifyingpixels representing the facet edges, generating a diagram of the gem,such that the diagram is a function of the pixels representing the facetedges, and superimposing the diagram onto the pixilated image.

In another embodiment of the invention, a computer based system andmethod are provided in which a pixilated image of a gem is obtained,facet dimensions are determined from the pixilated image, a region ofinterest in the pixilated image is designated, scripts are run toisolate inclusions within the designated region of interest,characteristics of the isolated inclusions are determined, and a claritygrade is generated based upon the determined characteristics.

In another embodiment of the invention, a computer-readable medium isprovided having computer-executable instructions thereon for renderingdigital content on a device. Included are computer-executableinstructions for obtaining a pixilated image of the gem from an imagingdevice, computer-executable instructions for deriving outlines of facetedges and corresponding facet dimensions from the pixilated image,computer-executable instructions for obtaining a designation of a regionof interest in the pixilated image, computer-executable instructions forrunning a plurality of scripts comprising different combinations ofvision analysis filters capable of isolating inclusions within thedesignated region of interest, computer-executable instructions fordetermining characteristics of inclusions isolated by the plurality ofscripts from pixels of the pixilated image corresponding to isolatedinclusions, and computer-executable instructions for generating aclarity grade based upon the determined inclusion characteristics.

As will be appreciated upon consideration of the following detaileddescription of the invention and accompanying drawings, there are manyadvantages and features of the present invention, which in turn lead tomany new and useful applications of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified flow diagram of operations involved indetermining the clarity grade of a gem in accordance with an embodimentof the invention.

FIG. 2A is a simplified flow diagram of operations involved in obtaininga pixilated image of a gem for purposes of clarity grading in accordancewith an embodiment of the invention.

FIG. 2B is a simplified illustration of an embodiment of an imagecapturing and processing configuration for obtaining a pixilated imageof a gem for purposes of clarity grading in accordance with anembodiment of the invention.

FIG. 3 is a flow diagram illustrating the generation of a gem diagramaccording to an embodiment of the invention.

FIG. 4 is an exemplary illustration of a screen configuration employedduring the acquisition of a pixilated digital image, and of an acquiredpixilated digital image of the type operated upon in embodiments of thepresent invention.

FIG. 5A is an exemplary illustration of an uncorrected gem diagramaccording to an embodiment of the invention.

FIG. 5B is an exemplary illustration of a corrected gem diagramaccording to an embodiment of the invention.

FIG. 5C is an exemplary illustration of a diagram of an ideal structurefor a gem according to an embodiment of the invention.

FIG. 5D is an exemplary illustration of a screen shot of an alternativescreen configuration displaying a pixilated image of a gem according toanother embodiment of the invention.

FIG. 6A is an exemplary top view illustration of a gem identifyinginclusion location identifier regions according to an embodiment of theinvention.

FIG. 6B is an exemplary illustration of a gem identifying a pavilionregion of the inclusion location identifier regions according to anembodiment of the invention.

FIG. 6C is an exemplary side view illustration of a gem inclusionlocation identifier regions according to an embodiment of the invention.

FIG. 7A is an exemplary illustration of an example of a screen shotdisplaying returned script results according to an embodiment of theinvention.

FIG. 7B is an exemplary illustration of an example of a screen shotdisplaying returned script results using a different screen layoutaccording to another embodiment of the invention.

FIG. 8 is a high level flow chart illustrating various functionalitiesprovided by an embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is directed towards providing an improved methodand system for analyzing a gem. More specifically, the present inventionprovides a method and system for utilizing a pixilated image to map agem and to determine various inclusion characteristics associated withthe gem, and for using of such characteristics to generate a claritygrade. Accordingly, the present invention has special utility in thefield of clarity grading. In addition, the present invention isparticularly suited for implementation in a computer application.

FIG. 1 provides an overview, by way of a simplified flow diagram, ofoperations involved in determining the clarity grade of a gem inaccordance with an embodiment of the invention.

To begin, in operation 10 an image is obtained of the gem to be gradedin a form which is or is capable of being pixilated, and a pixilatedimage is obtained. In operation 12, in an embodiment of the invention,information about the facets of the gem are obtained, and an outline ofthe facets of the gem may be created, from the pixilated image.Operation 12, will be described in further detail hereafter inconnection with FIGS. 3 through 5A-5C.

Preferably, in operation 14, a region of interest (“ROI”) is designatedby an operator or user. The pixels within the designated ROI are thenevaluated for inclusions. Operation 16 involves running analyses called“scripts” on the pixels within the region of interest in order toisolate any inclusions that may be located within the region ofinterest. These scripts are configured and selected for their ability toisolate typical types and patterns of inclusions in a pixilated image.Alternatively, and/or if needed, manual isolation of inclusions may beundertaken.

Following the isolation of the inclusions, operation 18 determinescharacteristics of the inclusions which were isolated in operation 16.As will be described in greater detail hereafter, such inclusioncharacteristics may include type, relative area, number, relief, andlocation (or position), among other characteristics. Blocks 20 and 22repeat operations 14, 16 and 18, as needed, to process the inclusions inthe gem. In block 20, if there are more inclusions to be characterizedin the current region of interest, operation 18 is repeated. If nofurther inclusions are to be characterized for the current region ofinterest, block 22 then determines if the are other regions of interestto be evaluated. If so, operation 14 is then accessed to permit thedesignation of a different region of interest for analysis, and thenoperations 16 and 18 are repeated as needed.

Once characteristics of the inclusions have been obtained, operation 24generates a clarity grade for the gem based upon the inclusioncharacteristics determined in the preceding operations.

A more detailed description will now be provided of the variousoperations identified in FIG. 1 .

Referring now to FIG. 2A, various steps involved in the obtain imageoperation 10 of FIG. 1 are depicted. In step 30 the operator starts upimage acquisition software, and powers-up the camera, or other imagingdevice. Software such as the application called Nikon Capture, availablefrom Nikon Corporation of Tokyo, Japan, can be used as the imageacquisition software when a still camera is being used. Next, in step32, a check is made of the size of the gem being imaged. Then it isdetermined whether the holder currently being used has the appropriateconfiguration for the gem being imaged. See step 34. If not, a moreappropriate holder is selected and installed, steps 36 and 38,respectively. Once an appropriate holder is in place, the gem iscleaned, and placed in the holder. See steps 40 and 42, respectively.

The “setup” referred to in FIG. 2A is an apparatus which supports andprovides illumination of the gem being analyzed. Preferably the setup isa dark field illumination apparatus that provides reflected dark fieldillumination, such as that described in co-pending U.S. Pat. Appln. No.12/287,188, now issued as U.S. Pat. 8,289,621 entitled “Reflected DarkField Method and Apparatus,” filed even date herewith, attorney docketnumber 353397-165953, and incorporated herein by reference in itsentirety. As described in the referenced application, reflected darkfield illumination is provided to illuminate the gem being imaged in amanner which minimizes direct (bright) reflections off of crown (orother face-up) facets and provides an increased light intensity levelwhich allows for faster shutter speeds and more ideal exposure settingswhen imaging gems. FIG. 2B illustrates a configuration of imagingdevice, lens, table, and stage, and which employs the reflected darkfield illumination, for obtaining a pixilated image of a gem forpurposes of clarity grading in accordance with an embodiment of theinvention. FIG. 2B is described in more detail in the above incorporatedby reference application.

Briefly, in FIG. 2B it can be seen that a table 2010 is supported abovea base 2012. A dark field illumination unit 2014, as described in theabove incorporated by reference application, is coupled to andpositioned below table 2010. Illumination control 2016 is provided bywhich the light sources within dark field illumination unit 2014 arecontrolled. Included are switches and intensity controls by which theoutput of various combinations of LEDs within dark field illuminationunit 2014 may be activated and/or adjusted. A pivoting structure 2018,as described in the above incorporated by reference application, iscoupled to a reflector unit 2020 which is positioned above table 2010.In FIG. 2B, reflector unit 2020 is shown in its down position, inregistration with dark field illumination unit 2014. Also shown in FIG.2B is a lens 2022 and imaging device 2024 supported above and inregistration with reflector unit 100. Imaging device 2024 is shownelectrically coupled to imaging device control 2028, which communicateswith computer 2030. The imaging device 2024 is supported by an imagingdevice mount 2032, which itself is supported by post 2034. Post 2034, inturn, is coupled to and supported by table 2010. With such aconfiguration, an operator is able to control the imaging device 2024 toview, capture, and store images of the gem under inspection, and tofurther process the captured images, such as in a clarity gradingoperation.

Returning to FIG. 2A, in step 44, the gem is arranged in the setup, andreflected dark field illumination is turned on. Then, in step 46, focus,magnification and position adjustments are made to optimize theconditions for capturing an image of the inclusions in the gem.Historically, the face-up position of a gem has been the mainobservation direction for visual clarity grading of all clarity gradesfrom VVS2 down. Therefore, the face-up position has been adopted as thepreferred observation direction for data collection and for takingdigital images in the preferred embodiment of the present invention.Other observation directions, such as those arrived at by tilting, addconsiderable complexity without offering a clear benefit, so these otherobservation directions while also possible alternatives for use inclarity grading, are not discussed in detail here.

In step 48, the imaging software is used in conjunction with the imagingdevice, such as a digital camera, to capture images of the gem. In step50, the captured images are saved, such as by storing the images on adisk or other media.

An exemplary illustration of a pixilated image 100 used in accordancewith the invention is provided in the screen shot of the imagingacquisition in FIG. 4 . As can be seen in the left hand side of thescreen shot, the imaging software provides various controls for theimage capture. For example, controls 102 relate to brightness, gain, andintegration time. Controls 104 relate to image sharpness as well asprovide a color space matrix.

Because the present invention involves extrapolating data from such apixilated image of a gem, obtaining a high quality digital image isimportant. As such, a brief discussion of several image-acquisitionissues which have been encountered is provided below.

Initially, the first digital images which were experimented with in thedevelopment of the invention were created by digitizing traditionalslides. Thereafter, a hardware setup, including a Model D1 digitalcamera by Nikon Corporation, of Tokyo, Japan, was used to provide ameans to make digital images of high resolution without any furtherprocessing. As a result of the camera’s sensor resolution, the generatedimages had about 6-7 micron pixels, which sets the threshold for clarityanalysis of high clarity diamonds. With such a sensor resolution,inclusions smaller than this threshold (such as a high VVS1 pinpoint),cannot be resolved, and even resolvable pinpoints can be difficult topick out on an image. Further, dust and grease can be mistaken for VVS1and WS2 pinpoints and feathers. These are some of the limitations of thetechnology. However, it is noted that when such a device is used toimage a diamond, and no inclusions can be resolved in the acquiredimage, this would be an indication that the diamond is a high claritydiamond. As imaging devices with sensors of better resolutioncapabilities become available, it is envisioned that such devices may beutilized to obtain digital images in accordance with the presentinvention.

The file size of digital images to be stored has also been an issue ofconcern because of the potential volume of images that need to becaptured. To keep the file size as small as possible (without losinginformation after compression of the original image), a JPEG 2000standard may be used. Different software plug-ins for this file formatexist from different manufacturers (for example, the LEAD Image BuilderPhotoshop plug-in, from Adobe Corporation, of San Jose, California, wasemployed here). In theory, the JPEG 2000 standard allows for compressingup to 95% without sacrificing pixel information. Alternatively, the morewidely used standard JPEG image format may also be employed.

A particular limitation of still photographs is that the properorientation of the diamond or other gem being imaged can only be checkedafter the image is shot. A real time camera, however, would acquireimages continuously while the diamond is being oriented allowing theprocess of setting up to take much less time because the image can bechecked continuously for better optimization of the image. Therefore, inanother embodiment of the invention, a real time camera, and real timecamera image acquisition software, , may be used as the imaging device,such as that available from RedLake, Inc. / IDT of Tallahassee, Florida.For example, the real time camera imaging device may be RedLake Inc. /IDT product model MegaPlus ES-4020 -color; having 2048 x 2048resolution, interline transfer CCD; 7.4 micron square pixels; a wellcapacity of 40,000 e - per pixel; a 60 percent fill factor; aprogressive scan; with clear glass filter; F-Mount lens adaptation; andcapable of 15 full frames per second. Accompanying the MegaPlus ES-4020are a camera head controller unit that provides CameraLink and FireWireinterfaces, and control software. Preferably, the real time camera isused with a NIKKOR 2.8 60 mm micro lens and NIKON PK 12 extension ring,manufactured by Nikon Corporation of Tokyo, Japan.

Returning to FIG. 1 , after obtaining a suitable digital image inoperation 10, the facets of the gem are mapped in operation 12. Furtherdetails of operation 12 are provided in FIG. 3 , which provides a blockdiagram for mapping a gem according to an embodiment of the invention.As illustrated, the process begins at step 60, wherein a pixilateddigital image of a gem is received, for example, the image 100 of FIG. 4. The gem images may be loaded from a designated file directory, forexample. Next, pixels representing the facet edges of the gem areidentified at step 62. Vision analysis software can be utilized to findall the facet edges of a gem for the surfaces through which the clarityanalysis is being conducted, for example all of the facet edges of aface-up diamond. Such software preferably uses edge detection techniquesand expected shape and facet distributions to fit a model to thedetected edges. Such vision analysis software may be based upon theLabVIEW application in the Vision Builder programming environment ofNational Instruments Corporation of Austin, Texas. From the identifiedfacet edges of the gem, a modeled outline (also referred to as a gemstructure diagram) is then generated in step 64, and superimposed ontothe actual digital image in step 66. The combination of actual image andsuperimposed modeled outline may then be used to measure the diameterand other dimensions (in pixels) of the gem and the area and otherdimensions of an inclusion, as well as to locate the position of aninclusion.

Uses of such collected information, in accordance with embodiments ofthe invention, are discussed in greater detail as a part of thedescription which follows of the determination of the relative size ofinclusions. Briefly, clarity grading typically considers the relativesize of an inclusion, for example, the relative area of an inclusion tothe area of a face-up gem. Therefore, measurements of the actual size ofinclusions are typically not a parameter of critical interest forclarity grading. For example, a small inclusion in a small diamond willtend to have more impact on the clarity than the same inclusion in alarger diamond. In accordance with a preferred embodiment of theinvention, in order to calculate the relative size of an inclusion, thearea of the inclusion and the area of the face-up diamond, for example,are measured such that the ratio of the inclusion area to diamond areacan be calculated. In this way, the size of the inclusion is calibratedrelative to the size of each diamond so they can be compared betweendiamonds.

In vision analysis software for a preferred embodiment of the invention,particular known dimensions of the gem (e.g., from precise laboratorymeasurement of diameter, which can have a precision to the thousandthsof a mm) are used so that the number of pixels per actual unit of lengthcan be calculated for each gem image. This allows the dataset derivedfrom images to be compatible with the dataset derived from non imagemeasurements, such as laboratory or operator measurements. For example,in the event an existing data base structure (database objects and datafields) is in the form of actual length or actual size, the calibrationof pixels per length dimension permits a conversion of pixel data (suchas number of pixels) into actual length and actual area form, or viceversa. Also, preferably, an operator may interactively measure face-upproportions of the gem, such as table size, pavilion/lower halve ratio,and star length ratio.

Returning now to the generation of a gem structure diagram in operation64 of FIG. 3 , several other features were implemented in connectionwith the development of that operation. For example, a correctionsub-program was developed in order to complete diagrams with missingedges and/or correct out of place intersections. FIG. 5A provides anexemplary illustration of an uncorrected gem diagram 400 superimposedonto a gem image 100, as may be output as an initial gem structurediagram in operation 64 of FIG. 3 . In the screen shot, it can be seenthat the generated uncorrected structure diagram 400 has an out-of-placeintersection 430. Preferably, the lower structure lines 420 of thediagram 400 are rendered to be readily distinguishable from the upperstructure lines 410, for example, by using various color combinationsand/or solid and dashed line combinations. Also visible is controlconsole 200 and summary field 300, as shown, by which features of theunderlying program are selected. Control console 200 may be configuredto permit, in addition to the “structure” function, selection of a“data” function, of an “ROI” function, a “scripts” function, a “facets”function, and a “manual draw” function, among others.

In FIG. 5B, an exemplary illustration of a corrected structure diagramaccording to an embodiment of the invention is provided. Within thisembodiment, a user selects correction box 210 to cause a correcteddiagram 500 to be displayed. As can be seen in FIG. 5B, correcteddiagram 500 includes corrected intersection 530. The correction of theintersection is achieved by a comparison between the modeled edges andthe facet edges detected by the Vision analysis software. In oneembodiment of the vision analysis software, edge detection analysisstarts with the outline of the gem, and works its way to the center ofthe gem using sweeps of conventional edge detection software tools. Thecorrection function preferably performs additional sweeps from inside tooutside, using the already found facet junctions as references.

FIG. 5C, illustrates another feature implemented in connection with thegeneration of a gem structure diagram which may be provided according toan embodiment of the invention -the generation of an “ideal” symmetrygem diagram. Within this embodiment, a user selects the box 220, labeled“Ideal,” in order to generate a diagram based upon the actual structurediagram obtained for the gem, for example diagram 400 of FIG. 5A, butwhich is further extrapolated to have perfect symmetry. This isillustrated as ideal structure diagram 600 in FIG. 5C. A comparison ofthe alignment of the lines of ideal structure diagram 600 with the facetedges in the pixilated image 100 reveals a number of locations wherethere are various degrees of misalignment. Therefore, the combined imagepermits the user to more easily identify where the structure of theactual gem departs from one that has perfectly symmetry.

FIG. 5D provides an exemplary screen shot of an alternative screenconfiguration displaying and processing a pixilated image of a gemaccording to another embodiment of the invention. Illustrated on theleft side of the screen shot are various controls. Control console 250permits the user to select between acquiring a new image, or opening anexisting one. Also, controls for saving data and canceling an operationare provided. Other buttons in control console 250 permit the user toselect between “Diagram” — which involves creation of a gem structurediagram, “Clarity” — which involves clarity analysis, or “Data” — whichinvolves access to a database and data entry for the gem beingprocessed. Gem information group 260 provides a data entry interface anddata displays of information relating to the gem being processed inconnection with the database. In gem information group 260, it can beseen that several tabs —“General”, “Database” and “Proportions” — areprovided for different information about the gem. The information thatmay be accessible through the “General” is illustrated in FIG. 5D. Forexample, for the gem having control number 999999999, the diameter —5.90 [mm], the shape —round, the image calibration for the image —170.28 [pixels/mm], and the weight— 0.70 [cts], of the gem are shown inFIG. 5D. The “Database” tab may provide access to other information toor from the database about the gem being processed. The “Proportions”tab may provide access to information about the cut proportions of thegem being processed. It is to be understood that pre-existing data fromthe database may be displayed, or new data obtained for the gem beingprocessed may be entered, by way of the gem information group 260.

Returning to FIG. 1 , once a gem structure diagram is generated andsuperimposed onto the pixilated image in operation 12, claritycharacteristics of the gem may then be mapped as a function of the gemstructure diagram. Operations 14 and 16 represent several of theoperations undertaken as a part of such mapping in accordance with anembodiment of the invention.

In the designated region of interest operation 14, an operatoridentifies a small region of the pixilated image where an inclusion ofinterest is located. Further image analysis is then performed on theidentified region. In particular, a region of interest (ROI) tool may beprovided by which an operator can draw a ROI boundary around a gradesetting inclusion to designate a subset of the pixilated image data foranalysis and to exclude extraneous data. The ROI may take the form of atwo-dimensional box defined by two points which is chosen by theoperator and which contains the grade setting inclusion.

Working with a ROI, instead of the whole image, also allows the imageanalysis to run much faster because there are far less pixels to processcompared to the entire image of the gem. In particular, use of the ROItool greatly simplifies the process of extracting inclusions from anentire diamond image, for example, which typically takes the form of amottled background full of bright reflections.

Following the designation of an ROI in operation 14, operation 16 ispreferably undertaken to isolate inclusions within the ROI. Thisinvolves running several vision analysis scripts in order to identifypixels representing the inclusions within the ROI, and displaying theresults for review by the operator. In a preferred embodiment, thevision analysis scripts are composed of a series of vision analysisalgorithms or filters. These algorithms/filters may then form a stringof tasks that can be run on an original digital image. When applied tothe original image, the goal of the script is to isolate the gradesetting inclusion from its surrounding region of interest. Preferably,the combinations of algorithms/filters used in the scripts are selectedfor their effectiveness in detecting the types of inclusions which aretypically encountered in clarity grading. Once isolated, the pixels thatrepresent the inclusion can be measured and analyzed in a later stage.

FIG. 7A provides an example of a screen shot of the inclusion analysisscreens that may be provided in an embodiment of the invention. Theselected region of interest 900 is displayed on the left side of thescreen. Inclusion 902 is visible within this image. In FIG. 7A, scriptresults 910 are exemplary illustrations of the results of running thevarious scripts according to an embodiment of the invention. Theoperator may then select the result of one of the scripts and save theresult, select a result and then edit it to best fit the inclusions, orsimply trace the feature manually if no result is acceptable. In FIG.7A, it can be seen that of the scripts shown, the script in upperright-hand corner appears to provide the best fit to the inclusion 902that appears in selected region of interest 900. It is noted thatseveral of the script result panes in FIG. 7A are blank. This may bebecause, for example, for the particular script the specified thresholdswere not met, or some other condition required by the particular scriptfor detection of an inclusion was not present in the pixel data forregion of interest 900. It is also to be noted that in addition to thescript results that are visible in FIG. 7A, additional scripts may berun and the script results presented to the operator by way of tabbedsets of results. In FIG. 7A the tabs labeled “Scripts 2”, “Scripts 3”,“Scripts 4”, and “Scripts 5” represent additional sets of scriptresults. It is also to be understood that the number of vision analysisscripts that are actually run depends upon how well the scripts performin isolating inclusions that typically are encountered. Poorlyperforming scripts may be eliminated so as to present the operator onlywith results from the best performing scripts. Once a suitable isolationof the inclusion is obtained, further calculations on the inclusions 902in the selected region of interest 900 are conducted.

A number of different scripts containing combinations of filters such asbrightness thresholds, hole filling routines, particle size filters, andedge detection filters among others have been developed in connectionwith the present invention. Specific implementations of these individualtypes of filters are available as built-in features of the IMAQ VisionBuilder software from National Instruments. In formulating scripts usedin the present invention, a number of these filtering techniques areapplied in succession to obtain the desired result. Once a particularcombination of filters is determined, the specific implementations ofthe selected filters can be selected in the IMAQ Vision Buildersoftware, and then integrated into the LabView software from NationalInstruments. An example of a combination and sequence of selected onesof these filters which can function as a script in accordance with thepresent invention is:

-   1) “Extract Color Planes” — flatten image from 3 color bands to 1    black and white;-   2) “Lookup Table: Square” — Apply square stretch to image;-   3) “Threshold: Manual” — Choose pre-selected thresholds, for    example, only include 165 to 255;-   4) “Particle Filter” — filter out clusters of pixels not between 5    to 50,000;-   5) “Advanced Morphology Label Objects” — identify each    non-contiguous object;-   6) “Advanced Morphology Remove Borders” — remove object touching the    edge of the ROI.

Another script example is:

-   1) Extract Color Planes: HSI — Intensity (flatten color image into    grayscale)-   2) Look - up Table: Square-   3) Image Mask: from ROI (region of interest)-   4) Threshold: Manual Threshold-   5) Advanced Morphology: Separate Objects-   6) Particle Filter-   7) Advanced Morphology: Label Objects-   8) Advanced Morphology: Remove borders

A further script example is:

-   1. Extract Color Planes: HSI— Intensity (flatten color image into    grayscale)-   2. Look - up Table: Square-   3. Image Mask: from ROI (region of interest)-   4. Threshold: Automatic Threshold-   5. Advanced Morphology: Fill Holes-   6. Advanced Morphology: Separate Objects-   7. Particle Filter-   8. Advanced Morphology: Label Objects-   9. Advanced Morphology: Remove borders

At first, 80 scripts were developed and organized into5 differenttabulated pages of script results, each containing 15 batches of scriptresults per page. A test was then conducted using about 80 selectedimages for the purpose of reducing the number of scripts to a morepractical number. The testing focused on the performance of eachindividual script ranked in terms of how broadly applicable each was tothe batch of images under test. Each script was also judged relative tothe cumulative performance of the most broadly applicable scripts. Inother words, consideration was given to how many additional inclusionswere successfully captured that were not already covered by highestranking scripts. This procedure insured that the performance of thevision analysis application continued to improve as more scripts wereadded. A performance key was assigned to each script and based on thisperformance key a ranking was made to determine what scripts performedbest. The ranking allows the best performing scripts to be placed on thefirst page and the worst to be deleted. The number of scripts waseventually reduced to 3 sets of 15 scripts.

The software that is used to outline facet edges and create diagrams ofthe diamonds may also help improve the performance of the clarityanalyzing scripts. Because some inclusions are difficult to separatefrom bright reflections at facet junctions, the diagram produced by thissoftware can be used to isolate the inclusions from the reflectivefacets. This function can either be turned on manually or automaticallybecause appending pieces of inclusion is a relatively quick and easyprocess.

FIG. 7B provides an example of a screen shot of a differentconfiguration of an inclusion analysis screen for displaying returnedscript results according to another embodiment of the invention. As withthe embodiment of FIG. 7A, the selected area of interest 900 andinclusion 902 of interest are displayed in the left side of the screen.Exemplary script results 910 are illustrated for “Scripts 1” of threepossible groups of scripts (“Scripts 1,” “Scripts 2,” and “Scripts 3”),as indicated by the labeled tabs. For the example shown, the differencesbetween the displayed script results 910 and the inclusion of interest902 may result in the operator electing to view script results forScripts 2 and/or Scripts 3, or, alternatively, to manually edit or tracethe overlay of the inclusion to provide a better fit.

On the lower left side of the screen shot of FIG. 7B, grouping 930provides information entry points and/or calculation results for theinclusion 902 of interest. Along the bottom of the screen a bar graph isprovided in chart 932 indicating the relative distance between thecenter of two adjacent clarity grades, for possible clarity grades ofVVS1, VVS2, VS1, VS2, SI1, SI2, I1, I2, and I3. In the bottom right handcorner of the screen, the results of the clarity analysis are displayedin section 934. The “clarity result” refers to the clarity gradecategory in which the particular gem has been assigned, and the“subclarity result” refers to the position of the particular gem withinthe range which makes up the assigned “clarity result.”

In other embodiments, the facet outlines may be merged with a graphicalrepresentation of the inclusion from the scripts to produce a plotsimilar to what is currently done manually by some graders. It has beennoted that although the area of the inclusion will be necessary forcalculating a clarity grade, only the outline needs to be plotted forinternal inclusions and a break line needs to be plotted for surfacereaching inclusions.

Returning to FIG. 1 , once the inclusion is suitably isolated, operation18 determines characteristics of the isolated inclusion from the pixelscorresponding to the isolated inclusion. Although any of severalinclusion characteristics may influence the ultimate clarity grade of agem, a few characteristics have been identified to be particularlyinfluential. Namely, the size, position, relief, number, and “type” of agem’s inclusions have been identified. Accordingly, a brief descriptionof each is provided below, along with a discussion of their respectivesignificance. Further, as determined by the methods and systemsdescribed herein, the numerical and other relationships for inclusionsand other clarity characteristics of a gem can be used to predict theinfluence of the inclusions or other clarity characteristic upon theclarity grade for the gem. Co-pending U.S. Pat. Appln. No. 12/287,187,now issued as U.S. Pat. 8,402,066 filed even date herewith, entitled “AMethod And System For Providing A Clarity Grade For A Gem,” attorneydocket number 353397-165955, and incorporated herein by reference in itsentirety, describes an approach which breaks down clarity grades intoseparate yet interacting inclusion parameters in order to predict aclarity grade based upon a set of inclusions parameters for a particulargem which may be obtained as described herein.

The size of an inclusion has the strongest overall impact on the claritygrade and the larger the inclusion, the greater the impact. The size ofan inclusion is represented in the face up view of a diamond as a twodimensional object. The length and width of a two dimensional inclusionmay be measured directly with a microscope equipped with a measuringgraticule. An equation of an ellipse, for example, may then be fed thesemeasurements and used to approximate the inclusion area. A certaindegree of error is associated with this approximation which is higherfor irregularly shaped inclusions, but with a sufficient quantity ofdata, errors can be smoothed out to produce general relationships thatcan be used to predict the influence of the face-up area of an inclusionon the clarity grade. This elliptical approximation of inclusion areahas been validated with similar results when using the digital imagingapproach described herein, that uses a more precise method whichdigitizes the outline of the inclusion, counts the number of pixelsinside the outline, and then converts the number of pixels into aninclusion size area or area relative to the size of the diamond. Thedigital imaging approach for determining the size of an inclusiondescribed herein is utilized in the preferred embodiment of theinvention.

An important aspect of the inclusion size parameter analysis is theconversion of the area of the inclusion to a ratio of the inclusion areato the size of the diamond. Experienced diamond graders have beenconsulted and confirm that the size of the diamond is considered in thedecision making process. Although most graders would agree thatsimilarly sized inclusions should not equally impact a 1.0 ct stoneversus a 10.0 ct stone, diamond graders cannot explain or predict, in ahypothetical sense, how the size of the diamond will influence theresults. They must first see an example and visually compare theinclusion size to the size of the diamond in order to confidentlyprovide a clarity grade.

The positioning of an inclusion can also influence the final claritygrade of a gem. In the face up view of a diamond, for example, a gradermay view and classify one of two inclusions differently even if bothinclusions are of similar relative sizes depending on their positionparameter. There are two main explanations for this. First, there is atendency for an inclusion to be more visible when it is located towardsthe center of the diamond (and thus also closer to the center of anobserver’s attention) as opposed to a location closer to the girdle. Asecond explanation is that a more explicit facet distribution and facetreflection pattern toward the edge of most diamonds may tend to hideinclusions, and reduce their visibility, making them less important.

The “relief” of an inclusion is a categorical measure of the contrastbetween the inclusion and the surrounding facet distribution andreflection pattern of a diamond. As a general rule, the brighter aninclusion is, the more visible an inclusion appears to be to the graderwho may lower the clarity grade as a result.

Many times one clarity characteristic will determine the clarity gradeof a diamond while other clarity characteristics in the stone will haveno significant impact on the final clarity grade call. The most severeclarity characteristic in a diamond is called the grade settinginclusion. The presence of multiple clarity characteristics of equalseverity to the grade setting inclusion can lower the clarity gradefurther. Face-up reflections of inclusions or mirror images can looklike additional inclusions to an observer and are therefore graded thesame as additional inclusions. Depending on the location of an inclusionin a diamond, the distribution of facets can cause the inclusion toappear multiple times or be reflected, especially when the inclusion ispositioned deep and near the culet of the diamond. Generally, the numberof inclusions has been found to have a minor role, but a sufficientquantity of additional inclusions of similar size or reflections ofinclusions can typically lower the clarity grade by a half a grade.

Clarity characteristics, classified according to their “type” havetypically been divided into two categories: internal and surfacereaching inclusions. Each of these categories may be further subdividedaccording to particular clarity grading procedures, into a number ofsubdivisions of “type” characteristics, some common and others uncommon.However, since many of the uncommon subdivisions such as chips, bruises,etc. are not believed to differ fundamentally from the more commonclarity characteristics such as crystals or feathers, the uncommoncategories may be lumped with the common ones.

With the foregoing in mind, operation 18 (FIG. 1 ) and the determinationof characteristics of the inclusion which has been isolated in operation16, will now be discussed in greater detail. Characteristics of theinclusions are determined by utilizing the pixels identified inoperations 14 and 16 as representing the inclusion.

The inclusion size parameter can be calculated by the summing of all thepixels within the inclusion area that are isolated by a script. Then acalculation can be made to find the inclusion area size relative to thesize of the diamond area (the calculation of which is based on thediameter). Preferably, a pixel-to-pixel calculation is made for thisdetermination of the relative size of the inclusion. In the controlconsole 920 illustrated in FIG. 7A, the operator may enter diameter datainto the diameter data field 922. As explained above, this diameter datais preferably from precise laboratory measurement of the diameter of thegem, which can have a precision to the thousandths of a mm. This permitscalculations in both pixel and length units to be made from thepixilated image data. From this information, calculations may beperformed which provide an image calibration (in pixels per mm), totalgem and inclusion areas (in mm²), and relative area. Preferably, theinclusion size or surface area (in pixels) and the diamond areas (inpixels) are measured first, and the digital images are calibrated usingthe input of the diamond diameter. With this information a calculationof inclusion size relative to the diamond size, and other sizeparameters, can be made. For example, the ratio of the inclusion sizearea (in pixels) to the total area of the diamond (in pixels), andinclusion area [mm], can be calculated. An example of the results ofsuch calculations can be seen in FIG. 7A in table 924. For the exampleprovided in FIG. 7A it can be seen that the entered diamond diameter[mm] is 6.60, the image calibration result [pixels per mm] is 174.82,the area [mm²] is 0.001047, and the area [%] is 0.003.

In the example of FIG. 7B, in grouping 930, the inclusion being analyzedhas been determined to have an area of 0.001 [mm²], to have a relativearea of 0.004 [%], to not have a “long” shape, to be a “crystal” type,to have a “relief” which is “low,” to be positioned in the crown, tohave no reflections, and to have been previously evaluated as a having aclarity of “VS1” and “High.” In the embodiment illustrated in FIG. 7B,the results appearing in the box labeled 934 are automatically generatedby the application. These results are then automatically copied in thebox in the left lower corner of grouping 930 for data base purposes.This entry can be changed by the operator.

Also, as part of operation 18 of FIG. 1 , other relevant pixel-relatedinclusion parameters such as location mapping of the inclusion, andrelief, can be determined or computed in a semi-automated way from theisolated inclusion and gem image pixel information.

In connection with a location mapping operation, position identificationguidelines were developed by which the positions (locations) ofinclusions or other clarity characteristics can be described, collectedand analyzed in a consistent way. In a preferred embodiment, fiveinclusion location identifier regions are employed: (1) “Table,” (2)“Table-Crown,” (3) “Crown,” (4) “Girdle,” and (5) “Pavilion.” FIGS.6A-6C, provide examples of the regions of a diamond structure thatcorrespond to these inclusion location identifier regions. The firstfour identifiers effectively divide the face-up area of a diamond intofour concentric rings, as illustrated in FIG. 6A. These rings aredefined from the center outward. In FIGS. 6A and 6C, Table 700references the “Table” region, which is centered in the table of thediamond and encompasses an area of about 80% of the total area of thetable. Table— Crown 710 references the “Table — Crown” transitionregion, which extends from the boundary of the “Table” region out toapproximately 50% of the star facets. Crown 720 references the “Crown”region, which extends from the boundary of the “Table-Crown” region toabout one-third of the upper girdle half. Girdle 730 references the“Girdle” region, which extends from the boundary of the “Crown” regionto the remainder of the girdle of the diamond. Finally, as illustratedin FIGS. 6B and 6C, Pavilion 740 references the “Pavilion” region, whichcorresponds to all of the pavilion side of the diamond. The foregoinginclusion location identifier regions can be correlated to the pixilatedimage and gem structure diagrams for a gem of interest. The inclusions,once isolated by operations 14 and 16, can then be sorted into locationsdefined by these inclusion location identifier regions: table,table-crown, crown girdle, or pavilion. The precise location of aninclusion is preferably determined by the digital gravity point of theinclusion’s pixels — the average of all pixel locations.

To determine an inclusion’s relief parameter, a pixel histogram of theinclusion may be measured relative to the histogram of the surroundingROI selection. The relief of the inclusion is then determined bymatching the relationship between the two histograms to one of a set ofreference images with known relief factors. Alternatively, the relief ofan inclusion may be calculated from the pixilated image data by usingthe ratio of the average pixel value within the inclusion to the averagepixel value of an area of the image with a constant radius surroundingthe inclusion.

As for the number of inclusions, although an automatic correction factorfor reflections may be implemented, the total number of inclusions mayalso be entered manually. The type of an inclusion may be enteredmanually as well.

Returning to FIG. 1 , once the characteristics of the isolated inclusionhave been determined in operation 18, operations 14-18 may be repeatedfor other inclusions within the currently designated region of interest,block 20. When all of the inclusions within a region of interest havebeen characterized, it is determined in block 22 whether there are moreregions of interest to be processed. If so, operations 14 - 20 arerepeated until all regions of interest have been processed. In operation24, the characteristics which have been determined for the inclusions ofinterest are then used to determine a clarity grade for the gem. Forexample, a clarity grade may be determined for the gem based upon therelative areas of the inclusions, the relief of the inclusions, thelocation of the inclusions, the “type” of the inclusions and/or thenumber of inclusions in the gem. The above referenced co-pending patentapplication number 12/287,187, now issued as U.S. Pat. 8,402,066entitled “A Method And System For Providing A Clarity Grade For A Gem,”attorney docket number 353397 - 165955, describes methodologies and asystem for parameterizing the inclusion and gem characteristics providedby the system and method of the present invention, and accounting forthe interrelationships of the parameterized inclusion properties toprovide a clarity grade result.

FIG. 8 shows a high level flow chart illustrating variousfunctionalities provided by an embodiment of the invention. Within suchembodiment, the procedure for analyzing a gem 1000 includes runningimage acquisition software at step 1010. Gem data is then entered atstep 1020, which may include the gem’s dimensions (e.g., diameter,weight, etc.) and/or control number. Next, a pixilated image file of thegem, obtained by the imaging software in step 1010, is opened at step1030. Then the facet edges of the gem may be outlined in step 1040.Alternatively, following step 1030, a modified step 1040 may beprocessed in which less than a full gem structure diagram is obtained,for example data sufficient to for image calibration (FIGS. 7A, 7B),and/or for correlating the position identifier regions 710 - 740 (FIG.6C) to the pixilated image.

Once step 1040 has been completed, an operator may select any of threetab selections at step 1050. The selections available in step 1050 are:CLARITY, DATA, or PROPORTIONS.

The CLARITY tab is selected to obtain a clarity grade. Such procedurebegins, for example, with activating the region of interest tool at step1100 and selecting a particular region of interest at step 1110. Aplurality of scripts for isolating inclusions within the region ofinterest are then run at 1120. At step 1130, the operator is permittedto determine whether any of the scripts are sufficient to satisfactorilyisolate the inclusions. If sufficient, the best performing script isselected at step 1132, otherwise the inclusion is manually outlined bythe operator at step 1134. The pixel-related inclusion characteristics(e.g., size, relief, and position) are then calculated and/or determinedby the procedure at step 1140. The operator enters inclusion type atstep 1150 and the number of reflections or additional inclusions at step1160. Then, a clarity grade is calculated at step 1170 (e.g., by using alook-up table or algorithm) and confirmed by the operator at step 1180.

The PROPORTIONS tab is selected in step 1050 in order to makeadjustments to the gem structure diagrams obtained from step 1040. Thisstep may be undertaken prior to selecting the CLARITY tab in order toverify that the gem structure diagrams acceptably depict the outlines ofthe gem’s facets. Upon selecting the PROPORTIONS tab, the operator ispresented with a number of choices in step 1200. The operator may, forexample, move the acquired image of the gem at step 1210 within theview; select the ideal symmetry structure box at step 1220 to cause agem structure diagram to be generated having ideal symmetry; zoom thegem image in/out at step 1230; correct the diamond outline (gemstructure diagram) at step 1240; correct the facet edges in the gemstructure diagram at step 1250; or correct the facet junction or culetposition in the gem structure diagram at step 1260.

Should the operator desire to obtain particular data pertaining to thegem, the DATA tab would be selected at step 1050, in order to proceed tostep 1300. By way of step 1300, the operator may either obtainpixel-related inclusion data (e.g., size, relief, or position) at step1320, or individual proportion data (e.g., star lengths, upper halflengths, table size, etc.) at step 1310.

As is apparent from the foregoing description of embodiments of thepresent invention, the various disclosed methods, operations or systemsmay be implemented in a conventional desktop or laptop computer coupledto a digital imaging device which is positioned to obtain images of agem supported and illuminated in an illumination apparatus such asdescribed herein. Further, many of the functionalities of the presentinvention provided for clarity measurements may be embodied in the formof executable computer code or instructions stored in acomputer-readable medium, such as a hard-disc, CDROM, DVD, memory card,USB memory module, semiconductor memory, and the like.

The present invention has been described above with reference to severaldifferent embodiments. However, those skilled in the art will recognizethat changes and modifications may be made in the above describedembodiments without departing from the scope and spirit of theinvention. Furthermore, while the present invention has been describedin connection with a specific processing flow, those skilled in the artwill recognize that a large amount of variation in configuring theprocessing tasks and in sequencing the processing tasks may be directedto accomplishing substantially the same functions as are describedherein. These and other changes and modifications which are obvious tothose skilled in the art in view of what has been described herein areintended to be included within the scope of the present invention.

What is claimed is:
 1. A method of obtaining a clarity grade for agemstone, comprising: by a computer, receiving a pixelated image of agemstone; by the computer, mapping, using the pixilated image of thegemstone, facets of the gemstone; by the computer, correcting the mappedfacets of the gem using a vision detection algorithm; by the computer,creating an outline of corrected, mapped facets from the pixelated imageof the gemstone; by the computer, receiving an indication of a region ofinterest in the pixelated image from a user input; by the computer,analyzing pixels in the region of interest; by the computer, identifyingany inclusions or inclusion reflections within the pixels in the regionof interest; and by the computer, determining a clarity grade based onthe analysis of pixels in the region of interest.
 2. The method of claim1 further comprising, by the computer, determining characteristics ofany inclusions found in the region of interest, based on the analysis.3. The method of claim 2 wherein the analysis of pixels includescounting a number of identified inclusions within the area of interest.4. The method of claim 2 further comprising, by the computer,determining an area of the identified inclusions within the area ofinterest; by the computer, determining a location for each of theidentified inclusions within the area of interest; by the computer,determining a relief for each of the identified inclusions within thearea of interest, and wherein the analysis of pixels includes area,location, and relief data.
 5. The method of claim 1 wherein the analysisof pixels includes at least one of brightness thresholds, hole fillingroutines, particle size filters, and edge detection filters.
 6. Themethod of claim 1 wherein the analysis of pixels includes, quantifying abrightness of the pixels corresponding to the inclusion, quantifying abrightness of pixels in a designated area adjacent the pixelscorresponding to the inclusion, and determining a relief characteristicfor the inclusion as a function of the brightness of the pixelscorresponding to the inclusion and of the pixels in the designated area.7. The method of claim 1 further comprising, by the computer, generatinga gemstone structure diagram for the gemstone from the pixilated imageof the gemstone.
 8. The method of claim 7 further comprising, by thecomputer, superimposing the gemstone structure diagram onto thepixelated image.
 9. The method of claim 1 wherein the pixelated image ofthe gemstone is generated from a digital camera and dark fieldillumination apparatus.
 10. The method of claim 9 wherein the dark fieldillumination apparatus includes intensity controls, a pivoting reflectorunit, and a table.
 11. A non-transitory computer-readable media toexecute the method comprising: by a computer, receiving a pixelatedimage of a gemstone; mapping, using the pixilated image of the gemstone,facets of the gemstone; correcting the mapped facets of the gem using avision detection algorithm; receiving an indication of a region ofinterest in the pixelated image from a user input; analyzing pixels inthe region of interest; identifying any inclusions or inclusionreflections within the pixels in the region of interest; and determininga clarity grade based on the analysis of pixels in the region ofinterest.
 12. The non-transitory computer-readable media of claim 11further comprising, determining characteristics of any inclusions foundin the region of interest, based on the analysis.
 13. The non-transitorycomputer-readable media of claim 12 wherein the analysis of pixelsincludes counting a number of identified inclusions within the area ofinterest.
 14. The non-transitory computer-readable media of claim 2further comprising, determining an area of the identified inclusionswithin the area of interest; determining a location for each of theidentified inclusions within the area of interest; determining a relieffor each of the identified inclusions within the area of interest, andwherein the analysis of pixels includes area, location, and relief data.15. The non-transitory computer-readable media of claim 11 wherein theanalysis of pixels includes at least one of brightness thresholds, holefilling routines, particle size filters, and edge detection filters. 16.The non-transitory computer-readable media of claim 11 wherein theanalysis of pixels includes, quantifying a brightness of the pixelscorresponding to the inclusion, quantifying a brightness of pixels in adesignated area adjacent the pixels corresponding to the inclusion, anddetermining a relief characteristic for the inclusion as a function ofthe brightness of the pixels corresponding to the inclusion and of thepixels in the designated area.
 17. The non-transitory computer-readablemedia of claim 11 further comprising, generating a gemstone structurediagram for the gemstone from the pixilated image of the gemstone. 18.The method of claim 17 further comprising, superimposing the gemstonestructure diagram onto the pixelated image.
 19. The method of claim 11wherein the pixelated image of the gemstone is generated from a digitalcamera and dark field illumination apparatus.
 20. The method of claim 19wherein the dark field illumination apparatus includes intensitycontrols, a pivoting reflector unit, and a table.